| //===- LoopUtils.h - Loop transformation utilities --------------*- C++ -*-===// |
| // |
| // Part of the MLIR Project, under the Apache License v2.0 with LLVM Exceptions. |
| // See https://llvm.org/LICENSE.txt for license information. |
| // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception |
| // |
| //===----------------------------------------------------------------------===// |
| // |
| // This header file defines prototypes for various loop transformation utility |
| // methods: these are not passes by themselves but are used either by passes, |
| // optimization sequences, or in turn by other transformation utilities. |
| // |
| //===----------------------------------------------------------------------===// |
| |
| #ifndef MLIR_TRANSFORMS_LOOP_UTILS_H |
| #define MLIR_TRANSFORMS_LOOP_UTILS_H |
| |
| #include "mlir/IR/Block.h" |
| #include "mlir/Support/LLVM.h" |
| #include "mlir/Support/LogicalResult.h" |
| |
| namespace mlir { |
| class AffineForOp; |
| class FuncOp; |
| class OpBuilder; |
| class Value; |
| |
| namespace loop { |
| class ForOp; |
| } // end namespace loop |
| |
| /// Unrolls this for operation completely if the trip count is known to be |
| /// constant. Returns failure otherwise. |
| LogicalResult loopUnrollFull(AffineForOp forOp); |
| |
| /// Unrolls this for operation by the specified unroll factor. Returns failure |
| /// if the loop cannot be unrolled either due to restrictions or due to invalid |
| /// unroll factors. |
| LogicalResult loopUnrollByFactor(AffineForOp forOp, uint64_t unrollFactor); |
| |
| /// Unrolls this loop by the specified unroll factor or its trip count, |
| /// whichever is lower. |
| LogicalResult loopUnrollUpToFactor(AffineForOp forOp, uint64_t unrollFactor); |
| |
| /// Get perfectly nested sequence of loops starting at root of loop nest |
| /// (the first op being another AffineFor, and the second op - a terminator). |
| /// A loop is perfectly nested iff: the first op in the loop's body is another |
| /// AffineForOp, and the second op is a terminator). |
| void getPerfectlyNestedLoops(SmallVectorImpl<AffineForOp> &nestedLoops, |
| AffineForOp root); |
| void getPerfectlyNestedLoops(SmallVectorImpl<loop::ForOp> &nestedLoops, |
| loop::ForOp root); |
| |
| /// Unrolls and jams this loop by the specified factor. Returns success if the |
| /// loop is successfully unroll-jammed. |
| LogicalResult loopUnrollJamByFactor(AffineForOp forOp, |
| uint64_t unrollJamFactor); |
| |
| /// Unrolls and jams this loop by the specified factor or by the trip count (if |
| /// constant), whichever is lower. |
| LogicalResult loopUnrollJamUpToFactor(AffineForOp forOp, |
| uint64_t unrollJamFactor); |
| |
| /// Promotes the loop body of a AffineForOp to its containing block if the |
| /// AffineForOp was known to have a single iteration. |
| LogicalResult promoteIfSingleIteration(AffineForOp forOp); |
| |
| /// Promotes all single iteration AffineForOp's in the Function, i.e., moves |
| /// their body into the containing Block. |
| void promoteSingleIterationLoops(FuncOp f); |
| |
| /// Computes the cleanup loop lower bound of the loop being unrolled with |
| /// the specified unroll factor; this bound will also be upper bound of the main |
| /// part of the unrolled loop. Computes the bound as an AffineMap with its |
| /// operands or a null map when the trip count can't be expressed as an affine |
| /// expression. |
| void getCleanupLoopLowerBound(AffineForOp forOp, unsigned unrollFactor, |
| AffineMap *map, SmallVectorImpl<Value> *operands, |
| OpBuilder &builder); |
| |
| /// Skew the operations in the body of a 'affine.for' operation with the |
| /// specified operation-wise shifts. The shifts are with respect to the |
| /// original execution order, and are multiplied by the loop 'step' before being |
| /// applied. |
| LLVM_NODISCARD |
| LogicalResult instBodySkew(AffineForOp forOp, ArrayRef<uint64_t> shifts, |
| bool unrollPrologueEpilogue = false); |
| |
| /// Tiles the specified band of perfectly nested loops creating tile-space loops |
| /// and intra-tile loops. A band is a contiguous set of loops. |
| LLVM_NODISCARD |
| LogicalResult tileCodeGen(MutableArrayRef<AffineForOp> band, |
| ArrayRef<unsigned> tileSizes); |
| |
| /// Performs loop interchange on 'forOpA' and 'forOpB'. Requires that 'forOpA' |
| /// and 'forOpB' are part of a perfectly nested sequence of loops. |
| void interchangeLoops(AffineForOp forOpA, AffineForOp forOpB); |
| |
| /// Checks if the loop interchange permutation 'loopPermMap', of the perfectly |
| /// nested sequence of loops in 'loops', would violate dependences (loop 'i' in |
| /// 'loops' is mapped to location 'j = 'loopPermMap[i]' in the interchange). |
| bool isValidLoopInterchangePermutation(ArrayRef<AffineForOp> loops, |
| ArrayRef<unsigned> loopPermMap); |
| |
| /// Performs a sequence of loop interchanges on perfectly nested 'loops', as |
| /// specified by permutation 'loopPermMap' (loop 'i' in 'loops' is mapped to |
| /// location 'j = 'loopPermMap[i]' after the loop interchange). |
| unsigned interchangeLoops(ArrayRef<AffineForOp> loops, |
| ArrayRef<unsigned> loopPermMap); |
| |
| // Sinks all sequential loops to the innermost levels (while preserving |
| // relative order among them) and moves all parallel loops to the |
| // outermost (while again preserving relative order among them). |
| // Returns AffineForOp of the root of the new loop nest after loop interchanges. |
| AffineForOp sinkSequentialLoops(AffineForOp forOp); |
| |
| /// Sinks 'forOp' by 'loopDepth' levels by performing a series of loop |
| /// interchanges. Requires that 'forOp' is part of a perfect nest with |
| /// 'loopDepth' AffineForOps consecutively nested under it. |
| void sinkLoop(AffineForOp forOp, unsigned loopDepth); |
| |
| /// Performs tiling fo imperfectly nested loops (with interchange) by |
| /// strip-mining the `forOps` by `sizes` and sinking them, in their order of |
| /// occurrence in `forOps`, under each of the `targets`. |
| /// Returns the new AffineForOps, one per each of (`forOps`, `targets`) pair, |
| /// nested immediately under each of `targets`. |
| using Loops = SmallVector<loop::ForOp, 8>; |
| using TileLoops = std::pair<Loops, Loops>; |
| SmallVector<SmallVector<AffineForOp, 8>, 8> tile(ArrayRef<AffineForOp> forOps, |
| ArrayRef<uint64_t> sizes, |
| ArrayRef<AffineForOp> targets); |
| SmallVector<Loops, 8> tile(ArrayRef<loop::ForOp> forOps, ArrayRef<Value> sizes, |
| ArrayRef<loop::ForOp> targets); |
| |
| /// Performs tiling (with interchange) by strip-mining the `forOps` by `sizes` |
| /// and sinking them, in their order of occurrence in `forOps`, under `target`. |
| /// Returns the new AffineForOps, one per `forOps`, nested immediately under |
| /// `target`. |
| SmallVector<AffineForOp, 8> tile(ArrayRef<AffineForOp> forOps, |
| ArrayRef<uint64_t> sizes, AffineForOp target); |
| Loops tile(ArrayRef<loop::ForOp> forOps, ArrayRef<Value> sizes, |
| loop::ForOp target); |
| |
| /// Tile a nest of loop::ForOp loops rooted at `rootForOp` with the given |
| /// (parametric) sizes. Sizes are expected to be strictly positive values at |
| /// runtime. If more sizes than loops are provided, discard the trailing values |
| /// in sizes. Assumes the loop nest is permutable. |
| /// Returns the newly created intra-tile loops. |
| Loops tilePerfectlyNested(loop::ForOp rootForOp, ArrayRef<Value> sizes); |
| |
| /// Explicit copy / DMA generation options for mlir::affineDataCopyGenerate. |
| struct AffineCopyOptions { |
| // True if DMAs should be generated instead of point-wise copies. |
| bool generateDma; |
| // The slower memory space from which data is to be moved. |
| unsigned slowMemorySpace; |
| // Memory space of the faster one (typically a scratchpad). |
| unsigned fastMemorySpace; |
| // Memory space to place tags in: only meaningful for DMAs. |
| unsigned tagMemorySpace; |
| // Capacity of the fast memory space in bytes. |
| uint64_t fastMemCapacityBytes; |
| }; |
| |
| /// Performs explicit copying for the contiguous sequence of operations in the |
| /// block iterator range [`begin', `end'), where `end' can't be past the |
| /// terminator of the block (since additional operations are potentially |
| /// inserted right before `end`. Returns the total size of fast memory space |
| /// buffers used. `copyOptions` provides various parameters, and the output |
| /// argument `copyNests` is the set of all copy nests inserted, each represented |
| /// by its root affine.for. Since we generate alloc's and dealloc's for all fast |
| /// buffers (before and after the range of operations resp. or at a hoisted |
| /// position), all of the fast memory capacity is assumed to be available for |
| /// processing this block range. |
| uint64_t affineDataCopyGenerate(Block::iterator begin, Block::iterator end, |
| const AffineCopyOptions ©Options, |
| DenseSet<Operation *> ©Nests); |
| |
| /// Tile a nest of standard for loops rooted at `rootForOp` by finding such |
| /// parametric tile sizes that the outer loops have a fixed number of iterations |
| /// as defined in `sizes`. |
| TileLoops extractFixedOuterLoops(loop::ForOp rootFOrOp, |
| ArrayRef<int64_t> sizes); |
| |
| /// Replace a perfect nest of "for" loops with a single linearized loop. Assumes |
| /// `loops` contains a list of perfectly nested loops with bounds and steps |
| /// independent of any loop induction variable involved in the nest. |
| void coalesceLoops(MutableArrayRef<loop::ForOp> loops); |
| |
| /// Maps `forOp` for execution on a parallel grid of virtual `processorIds` of |
| /// size given by `numProcessors`. This is achieved by embedding the SSA values |
| /// corresponding to `processorIds` and `numProcessors` into the bounds and step |
| /// of the `forOp`. No check is performed on the legality of the rewrite, it is |
| /// the caller's responsibility to ensure legality. |
| /// |
| /// Requires that `processorIds` and `numProcessors` have the same size and that |
| /// for each idx, `processorIds`[idx] takes, at runtime, all values between 0 |
| /// and `numProcessors`[idx] - 1. This corresponds to traditional use cases for: |
| /// 1. GPU (threadIdx, get_local_id(), ...) |
| /// 2. MPI (MPI_Comm_rank) |
| /// 3. OpenMP (omp_get_thread_num) |
| /// |
| /// Example: |
| /// Assuming a 2-d grid with processorIds = [blockIdx.x, threadIdx.x] and |
| /// numProcessors = [gridDim.x, blockDim.x], the loop: |
| /// |
| /// ``` |
| /// loop.for %i = %lb to %ub step %step { |
| /// ... |
| /// } |
| /// ``` |
| /// |
| /// is rewritten into a version resembling the following pseudo-IR: |
| /// |
| /// ``` |
| /// loop.for %i = %lb + %step * (threadIdx.x + blockIdx.x * blockDim.x) |
| /// to %ub step %gridDim.x * blockDim.x * %step { |
| /// ... |
| /// } |
| /// ``` |
| void mapLoopToProcessorIds(loop::ForOp forOp, ArrayRef<Value> processorId, |
| ArrayRef<Value> numProcessors); |
| } // end namespace mlir |
| |
| #endif // MLIR_TRANSFORMS_LOOP_UTILS_H |